
Lihu worked on backend and distributed deep learning systems, focusing on robust, maintainable solutions. For Furion-cn/sglang, Lihu refactored the SchedulePolicy component, introducing cache-aware and cache-agnostic Enum classes in Python to improve policy organization and validation, and added unit tests to ensure correctness and prevent misconfiguration. In yhyang201/sglang, Lihu implemented pipeline parallelism for Qwen2 and Qwen3 models using PyTorch, enabling model layers to be distributed across multiple devices for scalable inference. The work demonstrated depth in code refactoring, model parallelism, and distributed systems, establishing a foundation for future extensibility and production stability in both repositories.
May 2025: Delivered pipeline parallelism for Qwen2 and Qwen3 in yhyang201/sglang, enabling multi-device distribution of model layers and coordinated pipeline execution. Architectural refactor supports distributed layers and pipeline orchestration, laying the groundwork for scalable, high-throughput inference across multiple devices. Associated production-ready change tracked under commit 11553c1a3727ce20ca4b85ea767f46fcdcb7661d. No major bugs reported this month; validation pipelines and monitoring established to ensure stability as we scale.
May 2025: Delivered pipeline parallelism for Qwen2 and Qwen3 in yhyang201/sglang, enabling multi-device distribution of model layers and coordinated pipeline execution. Architectural refactor supports distributed layers and pipeline orchestration, laying the groundwork for scalable, high-throughput inference across multiple devices. Associated production-ready change tracked under commit 11553c1a3727ce20ca4b85ea767f46fcdcb7661d. No major bugs reported this month; validation pipelines and monitoring established to ensure stability as we scale.
January 2025 – Furion-cn/sglang: Delivered a SchedulePolicy refactor introducing cache-aware and cache-agnostic Enum classes, improving policy organization, validation, and robustness. Implemented enhanced policy validation/adjustment logic and added comprehensive unit tests to ensure correctness and maintainability. This work establishes a scalable scheduling configuration framework with clear traceability to commits and reduced risk of misconfiguration in production.
January 2025 – Furion-cn/sglang: Delivered a SchedulePolicy refactor introducing cache-aware and cache-agnostic Enum classes, improving policy organization, validation, and robustness. Implemented enhanced policy validation/adjustment logic and added comprehensive unit tests to ensure correctness and maintainability. This work establishes a scalable scheduling configuration framework with clear traceability to commits and reduced risk of misconfiguration in production.

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